library(tidyverse)
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library(p8105.datasets)
library(plotly)
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## layout
data(nyc_airbnb)
nyc_airbnb =
nyc_airbnb %>%
mutate(rating = review_scores_location / 2) %>%
select(
neighbourhood_group, neighbourhood, rating, price, room_type, lat, long) %>%
filter(
!is.na(rating),
neighbourhood_group == "Manhattan",
room_type == "Entire home/apt",
price %in% 100:500)
Plotly scatterplot
nyc_airbnb %>%
mutate(text_label = str_c("Price: $", price, "\nRating: ", rating)) %>%
plot_ly(
x = ~lat, y = ~long, type = "scatter", mode = "markers",
color = ~price, text = ~text_label, alpha = 0.5)
Plotly boxplot
nyc_airbnb %>%
mutate(neighbourhood = fct_reorder(neighbourhood, price)) %>% ## puts them in order of price instead of alphabetical
plot_ly(y = ~price, color = ~neighbourhood, type = "box", colors = "viridis")
Plotly barchart
nyc_airbnb %>%
count(neighbourhood) %>%
mutate(neighbourhood = fct_reorder(neighbourhood, n)) %>%
plot_ly(x = ~neighbourhood, y = ~n, color = ~neighbourhood, type = "bar", colors = "viridis")
ggplotly
scatter_ggplot =
nyc_airbnb %>%
ggplot(aes(x = lat, y = long, color = price)) +
geom_point(alpha = 0.25) +
coord_cartesian()
ggplotly(scatter_ggplot)
box_ggplot =
nyc_airbnb %>%
mutate(neighbourhood = fct_reorder(neighbourhood, price)) %>%
ggplot(aes(x = neighbourhood, y = price, fill = neighbourhood)) +
geom_boxplot() +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
ggplotly(box_ggplot)